数据融合：解决多源冲突
Data Fusion: Resolving Conflicts from Multiple Sources
摘要：
许多数据管理应用程序（如建立Web门户、管理企业数据、管理社区数据和共享科学数据）都需要集成来自多个源的数据。这些来源中的每一个都提供一组值，并且不同的来源通常可以提供冲突的值。为了向用户呈现高质量的数据，解决冲突并发现反映真实世界的值至关重要;此任务称为{ \em数据融合}。本文描述了一种新的方法，发现真正的价值，从冲突的信息时，有大量的来源，其中一些可能会从其他复制。我们提出了一个真实世界的数据的案例研究表明，所描述的算法可以显着提高真理发现的准确性，是可扩展的，当有大量的数据源。
英文摘要：
Many data management applications, such as setting up Web portals, managing enterprise data, managing community data, and sharing scientific data, require integrating data from multiple sources. Each of these sources provides a set of values and different sources can often provide conflicting values. To present quality data to users, it is critical to resolve conflicts and discover values that reflect the real world; this task is called {\em data fusion}. This paper describes a novel approach that finds true values from conflicting information when there are a large number of sources, among which some may copy from others. We present a case study on real-world data showing that the described algorithm can significantly improve accuracy of truth discovery and is scalable when there are a large number of data sources.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
